AI for hospitality
AI for hospitality
Every call answered, every booking confirmed, demand forecast from your own numbers. 5x ROI in 30 days, or we work free.
- Independent hotels
- Restaurant groups
- Event venues
- Resorts and lodges
- Golf and country clubs
Teams we build for
- Hoyes Michalos
- Nurse Next Door
- Fedi
- UBC Sauder
- Merchant House Capital
- Picton Investments
- Campbell Froh May & Rice LLP
- Barnakl
- Hungerford
- Breez
Teams we build for
- Hoyes Michalos
- Nurse Next Door
- Fedi
- UBC Sauder
- Merchant House Capital
- Picton Investments
- Campbell Froh May & Rice LLP
- Barnakl
- Hungerford
- Breez
Teams we build for
- Hoyes Michalos
- Nurse Next Door
- Fedi
- UBC Sauder
- Merchant House Capital
- Picton Investments
- Campbell Froh May & Rice LLP
- Barnakl
- Hungerford
- Breez
Missed calls are missed covers.
The phone rings during service, nobody answers, and the booking goes to whoever picks up.
The front desk does four jobs.
Check-ins, phones, emails and walk-ins, all at once, with the staffing you can actually get.
Pricing reacts too late.
The comp set moved Tuesday. Your rate moved Friday. The pickup you lost in between never shows up on a report.
The eight-top no-shows at 8:15.
The table sits empty through the turn while the waitlist from 5 o'clock eats somewhere else.
The group inquiry waits until Monday.
The wedding RFP lands Friday at 6pm. By Monday the couple has toured two other rooms and one of them answered first.
The property runs on whoever is on shift.
Late checkout on the third floor, the dog policy, the corkage rule. The guest gets a different answer depending on who picks up.
A general manager's Saturday
The morning starts at the front desk, not in the office
humanCheckout rush, 7:45. She works the desk line with the front office team. The phones do not stack up behind her, because the 6am shuttle question and two breakfast-hours calls were answered while the desk was two deep. Nobody was put on hold to protect a booking.
The night audit comes back summarized, exceptions on top
The audit from the PMS is read and condensed. Two rate overrides, one comp room, one folio dispute from a guest who says the minibar charge is wrong. Each exception carries the folio line it came from.
She rules on the folio dispute
humanShe comps the minibar charge and declines the parking refund, and the adjustment is drafted for the desk to post. Nothing was refunded by a machine. Money decisions stay hers, every time.
Confirmations and backfill work the restaurant book
Tonight's book gets confirmations, two cancellations are offered to the waitlist and taken, and the eight-top that booked twice under two names is flagged for the host stand instead of double-held.
The wedding RFP gets a drafted block
An RFP arrives through Cvent at noon for a September wedding. A room block draft and a banquet quote assemble from the rate rules and the event menus, then park for review. Nothing is sent. The date is held nowhere yet.
She prices the block herself
humanThe draft carries the dates, the room types and the menu math. She sets the block rate against what September is actually doing, trims the comp suite, and sends it under her name. Pricing a wedding is judgment. It stays judgment.
The flash report is built by the time she leaves
Occupancy and ADR from the PMS, covers from the Lightspeed terminal, tonight's no-show count, and the covers forecast for Sunday brunch, assembled into the owner flash with every number naming the system it came from.
Hospitality, before and after
The manual path is dashed: Calls ring out during service, No-shows found at seven, Rates set by gut feel. The system path replaces it, and a person approves before anything ships: Voice agent answers 24/7, Confirmations and backfill, Forecasts from your own numbers.
Before: by hand
- 01Calls ring out during servicehuman
- 02No-shows found at sevenhuman
- 03Rates set by gut feelhuman
After: the system
- 01Voice agent answers 24/7
- 02Confirmations and backfill
- 03Your approvalhuman
- 04Forecasts from your own numbers
The research
Accommodation and food services had the highest job vacancy rate of any Canadian sector in May 2026, 4.3% against 2.8% nationally (Statistics Canada, 2026, a vacancy rate, not turnover).
Statistics Canada · 2026 · Job Vacancy and Wage Survey and Survey of Employment, Payrolls and Hours, reference month May 2026, released July 30, 2026
Proof from the pattern
Prince of Travel, a travel media company, is a past Advizr client. The published case below shows the same pipeline and content mechanics. The hospitality-native numbers are what we would build and publish with you.
We guarantee 5x ROI inside 30 days of deployment, in writing, measured against a baseline you sign before we build. If the system misses the bar, we keep working for free until it clears.
The numbers in hospitality
Accommodation and food services had the highest job vacancy rate of any Canadian sector in May 2026, 4.3% against 2.8% nationally (Statistics Canada, 2026, a vacancy rate, not turnover).
Statistics Canada · 2026 · Job Vacancy and Wage Survey and Survey of Employment, Payrolls and Hours, reference month May 2026, released July 30, 2026
Restaurants deploying voice AI report 87% fewer missed calls and $3,000-$18,000 per month in recovered revenue per location (Hostie, 2025, vendor-reported).
Hostie · 2025
86%+ of hoteliers now depend on AI for demand forecasting (HSMAI Asia, 2025).
HSMAI Asia · 2025
Who this is built for
The first hour moves to the lobby
The audit used to be the first hour of your morning, folio by folio. Now it comes back summarized with the exceptions on top, the comp rooms, the rate overrides, the walk-in that paid cash. You rule on the two that need a ruling and spend the hour where the guests are. The property stops needing you in the back office to run the front.
The phone quits interrupting check-in
Every call answered on the second ring by an agent that says what it is, books the room, quotes the pet policy from your actual policy, and hands anything complicated to the desk with the context already captured. Your team gives the guest in front of them both hands.
Friday prep follows the book, not the gut
Covers forecast from your own history per location, confirmations and waitlist backfill shrinking the no-show hole before service, and the prep sheet drafted against the forecast instead of last Friday's memory. You still call the par levels. You just call them with the book in front of you.
The couple tours your room first
The RFP that lands Friday at 6pm has a drafted room block and a banquet quote waiting Saturday morning, built from your rate rules and your event menus. You review, price the parts that are judgment, and send. The couple tours your room before they tour anyone else's.
What stays human
- The morning starts at the front desk, not in the office
- She rules on the folio dispute
- She prices the block herself
The steps the day below leaves to a person, by design.
What we build for hospitality
Answer every call
Voice agent for reservations and FAQs.
Calls answered around the clock, bookings taken, hours and policies explained. Complex requests route to staff.
Group and event inquiry handling.
Event leads answered fast, quotes drafted for a manager to review and send.
Fill the book
Booking recovery and confirmations.
Confirmations, reminders and waitlist backfill that shrink the no-show hole in every service.
Guest messaging automation.
Pre-arrival, in-stay and post-stay messages, plus review requests, all consent-tracked under CASL.
Run the house by the numbers
Demand forecasting for prep and labour.
Covers and occupancy forecast from your own history, so the prep sheet and the 7shifts schedule start from the book instead of the gut.
Revenue-management support.
Rate suggestions assembled from your numbers and the market, and where IDeaS or Duetto is already running, the build reads their output instead of arguing with it. The manager sets the price.
Night audit and owner flash.
The audit summarized with exceptions on top, and the daily flash assembled from the PMS and the POS with every number naming its source.
The economics
Before and after economics
Line
- Phone, desk and admin hours in scope
Before
At the page defaults, 8 people spending 9 manual hours a week is 72 hours, $2,520 a week at $35 loaded cost.
After
The calculator below prices your own baseline, and the 5x ROI guarantee is measured against a baseline you sign before we build.
- Missed calls
Before
The phone rings during service and checkout, and the booking goes to whoever answers.
After
Every call answered and the booking taken. The vendor-reported recovery figures stay on this page's stat rail with their caveat, and your own recovered bookings are the measure.
- The no-show hole
Before
Found at seven, when the table sits empty through the turn.
After
Confirmations and waitlist backfill run on a schedule. Qualitative by design, your book is the measure.
- Demand and prep
Before
Rates and prep set by last week's gut feel while demand moved yesterday.
After
Forecast from your own covers and occupancy history. The adoption figure stays on the stat rail, and your prep sheet is the measure.
The dollar row is arithmetic on this page's calculator defaults, 8 people at 9 manual hours a week each at a $35 loaded hourly cost, which is 72 hours or $2,520 a week in scope. The missed-call and forecasting rows point at the Hostie and HSMAI stats on this page's rail without restating their numbers: the Hostie figures are vendor-reported, and the HSMAI figure measures adoption, not your result. The anchor case is adjacent, its published numbers are outbound mechanics for a lead-generation client, so no row in this table is a hospitality client outcome. The hospitality-native numbers are what we would build and publish with you.
Where the data comes from
PMS
Opera Cloud, Mews, Cloudbeds or WebRezPro holds the operating truth: reservations, folios, rate rules, housekeeping status and the night audit. The build reads it through the vendor's own API or scheduled report exports, and the flash, the forecast and the audit summary all cite it line by line.
Where it stops. Read-only. Nothing writes a rate, a folio adjustment or a reservation into the PMS. Refunds, comps and overrides are drafted for a person to post, and guest profiles never leave your accounts.
Booking channels
The book across every door it arrives through: SiteMinder feeding the OTA channels, Expedia and Booking.com among them, the restaurant book, and the event pipeline in Tripleseat. The system reconciles them against the PMS so one picture of tonight exists instead of four.
Where it stops. Watching and reconciling only. Nothing changes availability, price or inventory on any channel. Rate parity stays a human decision made inside your channel agreements, and a suggestion is the most the system ever produces.
Guest messaging
Pre-arrival notes, in-stay requests, post-stay review asks and the waitlist texts, running through Revinate or the inbox you already use. Voice sits beside it: calls answered, disclosed as automated, transcribed and filed against the reservation they belong to.
Where it stops. Consent-gated at the data layer. CASL consent state decides who can be messaged before any agent composes a word, unsubscribes are honored mechanically, recording is disclosed up front, and card numbers are never taken over the phone or in a thread.
How the system is built for hospitality
See the full capability mapRetrieval
Property information, rate rules and guest history indexed so an answer about a room, a policy or a past stay is grounded in your records. Guests notice immediately when it is not.
- pgvector
- Full-text BM25
- Reciprocal rank fusion
Agents and orchestration
Agents answer, confirm and follow up across voice and messaging on a schedule. Anything that changes a booking or charges a card is a proposal a person releases. Escalation to a human is one step, not a maze.
- agent-worker
- Autonomy guard
- Escalation handoff
Evaluation
Graded on real guest conversations your team already handled, scored for correctness and for tone. Voice is measured end to end including transcription error, because that is where these systems actually fail.
- Eval graders
- End-to-end voice grading
- quality-worker
Models
Speech and frontier language models for the conversational core. Ordinary time-series forecasting for occupancy and rate, which is a well-solved statistical problem and does not need a large model.
- Speech models
- Frontier models, one gateway, routed per task
- Time-series forecasting
Data boundary
Guest personal information and consent state stay in your accounts, scoped per property. Marketing consent is enforced in the data layer, not left to the agent's judgement.
- Supabase row-level security
- Consent ledger
- No-training API terms
PMS, Booking channels, Guest messaging feed a hybrid index. The agent runtime works from that index, and every consequential action passes a human approval before it reaches Ask your team, Your AI team, Workflow builder.
Your systems
- 01PMS
- 02Booking channels
- 03Guest messaging
The system
- 01Hybrid index
- 02Agent runtime
- 03Your approvalhuman
Where your team works
- 01Ask your team
- 02Your AI team
- 03Workflow builder
A general manager's Saturday
General manager runs the day through the built system: The morning starts at the front desk, not in the office, The night audit comes back summarized, exceptions on top, She rules on the folio dispute, Confirmations and backfill work the restaurant book, The wedding RFP gets a drafted block, She prices the block herself, The flash report is built by the time she leaves. Dashed steps stay with a person.
- 01General managerhuman
- 02The morning starts at the front desk, not in the officehuman
- 03The night audit comes back summarized, exceptions on top
- 04She rules on the folio disputehuman
- 05Confirmations and backfill work the restaurant book
- 06The wedding RFP gets a drafted block
- 07She prices the block herselfhuman
- 08The flash report is built by the time she leaves
Built around your rules
| Regime | What it demands here | How the system complies |
|---|---|---|
| PIPEDA and BC PIPA | Guest profiles, stay history and call recordings are personal information under both statutes, collected and safeguarded lawfully. | Guest data stays in your accounts, scoped per property at the database layer, under no-training API terms. |
| CASL | Pre-arrival notes, review asks and offers are commercial electronic messages needing consent, sender identification and a working unsubscribe. | Consent state is enforced in the data layer before any message is composed, the sender is identified, and unsubscribes are honored mechanically. |
| Call recording disclosure | A recorded reservation line must disclose recording and the agent must say what it is. | The voice agent identifies itself as automated and discloses recording up front, designed to Canadian privacy expectations. |
| Payments and PCI-DSS | Card data must be protected to PCI-DSS, including deposits taken by phone. | Card numbers never touch our systems and are never taken by the voice agent. Deposits and payments stay inside your processor, which publishes its own attestation. |
| Channel agreements and rate parity | OTA contracts constrain where and how your rates display, and a parity breach is a commercial dispute waiting to happen. | Nothing writes a rate to any channel. Rate work ends at a suggestion in front of your revenue manager, so parity stays a decision a person makes inside the agreements you signed. |
| Quebec Law 25 | Properties operating in Quebec carry consent, transparency and automated-processing disclosure duties beyond PIPEDA. | Consent and disclosure copy are scoped per province, and where Law 25 applies the build is designed to it before anything guest-facing ships. |
The regimes that govern hospitality, what each demands, and how the system complies
Regime
- PIPEDA and BC PIPA
What it demands here
Guest profiles, stay history and call recordings are personal information under both statutes, collected and safeguarded lawfully.
How the system complies
Guest data stays in your accounts, scoped per property at the database layer, under no-training API terms.
- CASL
What it demands here
Pre-arrival notes, review asks and offers are commercial electronic messages needing consent, sender identification and a working unsubscribe.
How the system complies
Consent state is enforced in the data layer before any message is composed, the sender is identified, and unsubscribes are honored mechanically.
- Call recording disclosure
What it demands here
A recorded reservation line must disclose recording and the agent must say what it is.
How the system complies
The voice agent identifies itself as automated and discloses recording up front, designed to Canadian privacy expectations.
- Payments and PCI-DSS
What it demands here
Card data must be protected to PCI-DSS, including deposits taken by phone.
How the system complies
Card numbers never touch our systems and are never taken by the voice agent. Deposits and payments stay inside your processor, which publishes its own attestation.
- Channel agreements and rate parity
What it demands here
OTA contracts constrain where and how your rates display, and a parity breach is a commercial dispute waiting to happen.
How the system complies
Nothing writes a rate to any channel. Rate work ends at a suggestion in front of your revenue manager, so parity stays a decision a person makes inside the agreements you signed.
- Quebec Law 25
What it demands here
Properties operating in Quebec carry consent, transparency and automated-processing disclosure duties beyond PIPEDA.
How the system complies
Consent and disclosure copy are scoped per province, and where Law 25 applies the build is designed to it before anything guest-facing ships.
Guest data and call recordings stay inside your accounts, with consent tracked CASL-first and recording disclosed up front.
The objections
OpenTable already sends confirmations. What is left to automate?
Confirmations are the smallest piece. OpenTable and SevenRooms confirm the bookings they hold. They do not answer the phone during service, backfill a cancellation from the waitlist, chase the double-booked eight-top, draft the banquet quote, or reconcile the book against the PMS and the POS into one flash. The build sits on top of the book you keep, and replaces the assembly around it.
Saturday night is chaos. No system survives contact with service.
It is not on the floor. It works the phone, the book and the paperwork so the floor gets your people. During the rush it answers the calls nobody can take, holds the messages that can wait, and flags only what needs a decision tonight. The chaos is exactly why the phone should not be one of the four jobs the desk is doing.
Every location runs differently. A group rollout will flatten what works.
The rules are per location. One room's waitlist policy, deposit rule and quiet Tuesday are its own, set by its manager, not inherited from the busiest store. We start with one location, measure against its baseline, and the second location copies the mechanics, never the settings.
We staff lean on purpose. Nobody here can own an AI system.
Nobody has to become one. You run the hardest sector in the country to staff, so the rules live in the workspace, written in plain language your next manager can read, not in a departed GM's head. Advizr builds, monitors and maintains the system, and the guarantee is measured on your baseline, not on how much of our software your team babysits.
We fly a flag. The brand decides our tech stack.
The PMS the brand mandates stays exactly where it is. The build reads it through its own reports and APIs and writes nothing back to it, no rate, no folio, no reservation. What we automate is the work around the mandated stack, the phone, the follow-ups, the flash, which no flag standard reaches.
How we build it for hospitality
Start where the phone goes unanswered.
After-hours and overflow contact is measurable from day one and carries the least risk. We record the baseline miss rate before anything changes.
Grade voice end to end, including transcription.
Voice systems fail at the transcription boundary, not in the language model. Booking accuracy and misroute rate are measured on real recorded calls before the phones switch over.
Add revenue work once guests trust the channel.
Occupancy and rate forecasting is a mature statistical problem. It follows the guest-facing work rather than leading it.
What we will not automate
Changing a booking or charging a card. Escalation to a person is one step, never a maze.
What that means in practice
Agents and orchestration
AI that does the work instead of just answering: looks things up, calls your systems, completes multi-step tasks, and knows when to hand off to a human.
Where we stop. Multi-agent swarms are oversold; most jobs need one well-guarded loop. If a cron job and a script solve it, that is what we build, because 90 percent per-step accuracy compounds to 59 percent over five chained steps and no framework changes that arithmetic.
Vision, documents and speech
AI for eyes and ears: reading documents, watching camera feeds, transcribing calls.
Where we stop. Bespoke computer vision is justified by volume and latency, not by novelty. Below that bar, a vision-language model on demand is cheaper to run and easier to maintain, and we will tell you which side of the bar you are on before anything is built.
Classic and predictive ML
Not every problem needs a language model. Predicting numbers, churn, demand, fraud risk, is usually solved better, cheaper and more explainably with proven statistical ML.
Where we stop. When the input is language, judgment or unstructured documents, classic ML underperforms and we say so. The discipline runs both ways: if your problem is a prediction problem, you will hear that it does not need an LLM from us before you pay for one.
Where your team works
Tour the platformAsk your team
Chat with a team that already knows your business.
Every agent is briefed on your documents, your data, and your preferences. Ask for the number, the draft, or the plan and cite where it came from.
Your AI team
A roster, not a black box.
Every agent on your account is named, scoped, and inspectable: what it does, what it may touch, and what it has done lately.
Workflow builder
Describe the workflow. Watch it assemble.
Say what should happen in plain language and the builder assembles the automation on a canvas you can read, run, and change.
Cost per outcome
Every dollar of spend traced to the work behind it.
Outcomes delivered, cost per outcome, value attributed, return on spend. The same measurement the guarantee is settled against, live on one page.
By team
The same system, seen from the desk that runs it.
Run your numbers.
Your operations
Savings use the low end of our hours-reclaimed range. The math is conservative on purpose.
The math
Calculated at the low end of every range.
Every first build is covered in writing: 5x ROI in 30 days. Or we work for free.
The hard questions
Free · 3-5 days
Know your number in five days.
We map your operations, find the highest-ROI automations, and hand you a ranked plan with the payback math attached. Yours to keep, whoever builds it.
Prefer to talk first? Book 15 minutes with James. No pitch deck.